class_docstr: Main coreference resolution algorithm
docstr: Find a most representative mention for each cluster
  
  Return:
      Dictionnary of {original_mention: most_representative_resolved_mention, ...}
docstr_tok: ["Find","a","most","representative","mention","for","each","cluster","Return",":","Dictionnary","of","{","original_mention",":","most_representative_resolved_mention",",","...","}"]
code: def get_most_representative(
      self, last_utterances_added=True, blacklist=True
  ):
      """
      Find a most representative mention for each cluster
  
      Return:
          Dictionnary of {original_mention: most_representative_resolved_mention, ...}
      """
      clusters, _ = self.get_clusters(
          remove_singletons=True, blacklist=blacklist
      )
      coreferences = {}
      for key in self.data.get_candidate_mentions(
          last_utterances_added=last_utterances_added
      ):
          if self.mention_to_cluster[key] is None:
              continue
          mentions = clusters.get(self.mention_to_cluster[key], None)
          if mentions is None:
              continue
          representative = self.data.mentions[key]
          for mention_idx in mentions[1:]:
              mention = self.data.mentions[mention_idx]
              if (
                  mention.mention_type
                  is not representative.mention_type
              ):
                  if mention.mention_type == MENTION_TYPE["PROPER"] or (
                      mention.mention_type == MENTION_TYPE["NOMINAL"]
                      and representative.mention_type
                      == MENTION_TYPE["PRONOMINAL"]
                  ):
                      coreferences[self.data.mentions[key]] = mention
                      representative = mention
  
      return coreferences
  
imports: import os
  import spacy
  import numpy
  from neuralcoref.train.utils import PACKAGE_DIRECTORY, SIZE_SINGLE_IN
  from neuralcoref.train.compat import unicode_
  from neuralcoref.train.document import Document, MENTION_TYPE, NO_COREF_LIST
label_desc: Use image node_id 15 for calling the Coref obj's underlying member method code with example usage: obj.get_most_representative(last_utterances_added, blacklist) and returns: coreferences